Many common diseases, although familial, appear not to follow simple modes of inheritance. In some cases the inheritance may be simple, but nongenetic factors affect the phenotypes, thereby obscuring the genetic pattern. For example, environmental factors which affect the phenotype may aggregate in families, resulting in nongenetic familiality. Pleiotropic genes may produce inconsistent effects on multiple phenotypes. Assortative mating may produce more offspring resembling their parents than expected assuming random mating. Phenotypic expression may require an environmental stimulus, resulting in reduced penetrance in its absence. Aging may promote expression of the phenotype, mimicking reduced genetic transmission to offspring. The expression of the same genotype may differ between males and females. Unless the analyses of such phenotypes assume models which include these nongenetic factors, the genetic effect may be undetectable or falsely inferred. This application proposes to develop, implement, and apply genetic models used to detect major genes in the presence of nongenetic factors. The implementation will occur in PAP, a Fortran program for likelihood analysis. The extensions proposed include regressive models for univariate and multivariate phenotypes, age of onset curves, and unequal variances across PAP for other users will be continued.